The “Restless Allure” of (Architectural) Form: Space and Perception between Germany, Russia, and the Soviet Union
Bibliographic record
Abstract
This essay – as well as Luka Skansi, Teaching Architecture: “Space”, the Basic Course at Vchutemas, “Casabella”, ISSN 0008-7181, Mar. 2015, year 79, iss. 847, pp. 4-19, 108-111 – is the outcome of research conducted on the Schickler-Lafaille Collection at the CCA – Canadian Centre for Architecture. In the collection, we find a valuable photographic fund which documents the experimental work conducted within the VKhUTEMAS classrooms, one of the main Soviet educational institutions following WWI, and the place where 20th-century Soviet architectural culture was formed. The collected works comprise a vast selection of images depicting models and drawings produced by students of the 'Space' course taught by architect Nikolaj Ladovskij and assisted by Vladimir Krinskij and Nikolaj Dokuchaev, one based on the renowned psychoanalytical method. \nThe course was part of the so-called Osnovno otdelenie, the preliminary course program, and was regarded a fundamental step in the educational system and a key opportunity to direct students’ attention to the more general problems of architecture, rather than demanding their immediate involvement in more specialised disciplinary tracks. \nThe essay depicts the origins of teaching techniques in German art history and philosophy, in the so-called Munich Formalist school, where many Russian-Soviet artists and art theorists were formed before the First World War (Vladimir Favorskij, Aleksander Gabričevskij, Naum Gabo, Igor Grabar, and many others).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".